← BioTransfer GEO Dataset Finder
GEO series

Non-coding genetic variants dominant in African American reveal prostate cancer risk

GSE276748 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing 8 samples Submitted 2025/08/19 Platform GPL30173
Summary
Prostate cancer (PrCa) manifests substantial variation in incidence rates among distinct populations. African American (AA) men are more likely to be diagnosed with and die from PrCa than European American (EA) men. Despite ongoing advancements in identifying polygenic risk variants from large genome-wide association study (GWAS) cohorts, the genetic mechanisms underlying the higher prevalence of PrCa in AA men remain unclear. A systematic approach that does not rely on extensive cohorts to identify causal regulatory variants contributing to PrCa development is still lacking. Here, by employing a sequence-based deep learning model of prostate regulatory enhancers, we identified ~2,000 essential SNPs (eSNPs) with increased alternative allele frequency in AA and which potentially affect the enhancer function leading to greater PrCa susceptibility. The identified eSNPs potentially mediate PrCa development through two complementary mechanisms: alternative alleles with increased enhancer activity are associated with immune system suppression, while those with decreased enhancer activity are linked to differentiation processes. Interestingly, the eSNPs disrupt the binding of key prostate transcription factors including FOX, AR and HOX families, collectively contributing to PrCa predisposition. Together these eSNPs can be used to assess polygenic risk score that is more effective than previous GWAS-based risk scores in distinguishing individuals with PrCa from the control.
Published in
Non-coding genetic variants underlying higher prostate cancer risk in men of African ancestry
Li S, Fatema K, Sundarraj N et al. · Nature communications 2025 · PMID 41266362 · doi:10.1038/s41467-025-64631-4
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE276748_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 8 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1158792 and SRA study SRP531582. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 8 more — browse all 8 samples with per-sample file links →

Similar datasets

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.